During the past years, systems for scanning the surface of moving objects have been developed and applied for grading, sorting or quality control purposes in many high volume manufacturing applications such as found in the automotive, consumer electronics, agricultural, food or wood and lumber processing industries. Such scanning systems typically use digital cameras for detecting reflection-related characteristics of the surface of objects under inspection, which cameras can also be used as profile sensors based on laser triangulation to measure geometrical and other 3D surface characteristics of the inspected objects. In some applications, many characteristics of the object surface must be detected, thus requiring integration of several optical scanning sensors using associated lighting devices and whose outputs are combined for the desired purpose. A known defect detection system for lumber using that approach is disclosed in U.S. Pat. No. 5,960,104 to Conners et al., wherein color cameras are employed to detect surface features, and a laser profiling device is employed to perform three-dimensional (3D) shape detection. However, the integration of several sensors generally increases complexity, dimensions and cost of the scanning system.
In some prior known scanning apparatus, each scanning unit includes a digital camera associated with a single laser directing a linear-shaped laser beam onto the board surface under inspection, to form a laser line that intersects the field of view of the camera, which is capable of generating a 3D profile image of the board surface through a laser triangulation technique based on detected position of the laser line. Furthermore, to provide scanning unit compactness, it is known that from the same imaging sensors (CMOS or CCD) provided on such 3D digital camera, it is possible to simultaneously generate a 2D image of the same board surface from the measured mean intensities of the reflected laser line. Moreover, a linear laser source can also be used to provide lighting in cases where only 2D imaging is required. Typically, a 2D image can be expressed in terms of a plurality of line image vectors forming a matrix with reference to orthogonal first and second axis X and Y, such as obtained while moving the inspected object (or the camera) relative to the camera (or the object) along Y axis, while performing laser scanning using a linear laser source that extends along X axis. Such 2D image can also be represented as a plurality of column image vectors extending along Y axis forming the same matrix. In practice, the measured variation between successive values of column image vectors is mainly associated with corresponding changes in reflectance characteristics of the scanned surface. However, the measured variation may also be influenced by low frequency noise along scanning direction X caused by irregularity of illumination that may be due to imperfections of the source of linear light, especially in the case of a laser source, or to a misalignment of the linear light source with respect to the scanned surface orientation. In attempting to filter that noise using conventional known techniques, it is difficult to do so without adversely affecting the portion of image data representing actual changes in reflection characteristics of the scanned surface.
Therefore, there is a need for improving techniques for filtering low frequency noise in images obtained with linear light scanning.